class_docstr: Tests the correctness of the Y = g(X) = Log[1 + exp(X)] transformation.
code: def testScalarCongruencyWithNegativeHingeSoftness(self):
      bijector = softplus.Softplus(hinge_softness=-1.3)
      bijector_test_util.assert_scalar_congruency(
          bijector,
          lower_x=-2.0,
          upper_x=2.0,
          eval_func=self.evaluate,
          rtol=0.02,
      )
  
imports: from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import bijector_test_util
  from tensorflow_probability.python.bijectors import softplus
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 12 for calling the SoftplusBijectorTest obj's underlying member method code with example usage: obj.testScalarCongruencyWithNegativeHingeSoftness() without return types